Conductance Model for Extreme Events : Impact of Auroral Conductance on Space Weather Forecasts

Abstract

Ionospheric conductance is a crucial factor in regulating the closure of magnetospheric field-aligned currents through the ionosphere as Hall and Pedersen currents. Despite its importance in predictive investigations of the magnetosphere-ionosphere coupling, the estimation of ionospheric conductance in the auroral region is precarious in most global first-principles-based models. This impreciseness in estimating the auroral conductance impedes both our understanding and predictive capabilities of the magnetosphere-ionosphere system during extreme space weather events. In this article, we address this concern, with the development of an advanced Conductance Model for Extreme Events (CMEE) that estimates the auroral conductance from field-aligned current values. CMEE has been developed using nonlinear regression over a year's worth of 1-min resolution output from assimilative maps, specifically including times of extreme driving of the solar wind-magnetosphere-ionosphere system. The model also includes provisions to enhance the conductance in the aurora using additional adjustments to refine the auroral oval. CMEE has been incorporated within the Ridley Ionosphere Model (RIM) of the Space Weather Modeling Framework (SWMF) for usage in space weather simulations. This paper compares performance of CMEE against the existing conductance model in RIM, through a validation process for six space weather events. The performance analysis indicates overall improvement in the ionospheric feedback to ground-based space weather forecasts. Specifically, the model is able to improve the prediction of ionospheric currents, which impact the simulated dB/dt and ΔB, resulting in substantial improvements in dB/dt predictive skill.Plain Language Summary Electric currents generated in the Earth's space environment due to its magnetic interaction with the Sun leads to charged particle deposition and closure of these currents in the terrestrial upper atmosphere, especially in the high-latitude auroral region. The enhancement in the electrical charge-carrying capacity as a result of this process in the Earth's upper atmosphere, also known as the ionosphere, is challenging to estimate in most numerical simulations attempting to study the interactive dynamic and chemical processes in the near-Earth region. The inability to accurately estimate this quantity leads to underprediction of severe space weather events that can have adverse impacts on man-made technology like electrical power grids, railway, and oil pipelines. In this study, we present a novel modeling approach to address this problem and provide global simulations with a more accurate estimate on the electrical conductivity of the ionosphere. Through this investigation, we show that the accurate measurement of the charge carriers in the ionosphere using the new model causes substantial improvements in the prediction of space weather on the ground, and significantly advances our understanding of global dynamics causing ground-based space weather.

Numerical Simulations of the Geospace Response to the Arrival of an Idealized Perfect Interplanetary Coronal Mass Ejection

“…The former is achieved via an empirical function of solar zenith angle and F10.7 solar radio flux (Moen & Brekke, 1993). The latter is set by an empirical function of the local Birkeland current strength (Mukhopadhyay et al., 2020; Ridley et al., 2001). To better capture ring current dynamics, the Rice Convection Model (RCM) (Harel et al., 1981; Sazykin & Stanislav, 2000; Toffoletto et al., 2003) is also employed.…”

“…The SWMF has been validated in terms of magnetospheric dynamics (Rastätter et al., 2011; Ridley et al., 2002; Welling & Ridley, 2010; Welling et al., 2015), Birkeland current distributions (Korth et al., 2011), ground magnetic perturbations (Yu & Ridley, 2008, 2009b), and associated geomagnetic indices (Glocer, 2016; Haiducek et al., 2017; Rastätter et al., 2013). The finer spatial grid resolution used in this study greatly improves data‐model comparisons in terms of auroral electrojet index performance (Haiducek et al., 2017), Birkeland current morphology (e.g., Welling et al., 2015), and integrated Birkeland current strength (Mukhopadhyay et al., 2020), overcoming some of the limitations explored in Anderson et al. (2017).…”

“…Again, the situation is improved for the finer grid resolution employed in this study. For example, the Heidke Skill Score for at the 1.5 nT/s threshold improves from 0.318 (i.e., the model captures 31.8% of threshold crossings not captured by random guessing) to 0.4094 (Mukhopadhyay et al., 2020). It is critical to recognize that these scores encompass all activity, including periods when the model struggles, such as substorms (e.g., Haiducek et al., 2020).…”

The Case for Improving the Robinson Formulas

“…They included two different settings of a background offset value for the conductance, in addition to the FAC‐driven conductance settings, a technique similar to Ridley et al (2004). In a direct follow‐on to Ridley et al (2004), Mukhopadhyay et al (2020) modified the methodology and expanded the dataset to a full year of AMIE results—all of 2003, which included several superstorms—to create a model of the FAC‐conductance relationship applicable to extreme event conditions. Another relationship between FACs and conductance has been created by Robinson et al (2020), who used nine storm days of Poker Flat Incoherent Scatter Radar (PFISR) observations with AMPERE‐derived FACs.…”

Determination of Auroral Electrodynamic Parameters From AMPERE Field‐Aligned Current Measurements

“…More recently, Mukhopadhyay et al. (2020) have refined the approach introduced by Ridley et al. (2004), who used results from numerical models to establish relationships between field‐aligned currents and conductances.…”